Check for better agreement after removing the major sources of variance
42 features that were were identified by variance explained were deleted from a fresh data frame and TSNE was applied to the reduced feature set. Further below those particular features are examined more closely
Only 6 features are left, suggesting many dimensions where models and data disagree
cohen score is : D = -0.15 Spikecount_stimint_1.5x
cohen score is : D = -0.64 initburst_sahp_vb_1.5x
cohen score is : D = 0.05 Spikecount_stimint_3.0x
cohen score is : D = 0.59 input_resistance
Features with high agreement between models and data¶
<Figure size 432x288 with 0 Axes>
-27354.21648389174
cohen score is : AP1RateOfChangePeakToTroughTest_3.0xD = -1.05
272.42181591323225
cohen score is : sag_ratio1_3.0xD = 1.17
19334.458745961303
cohen score is : ISICVTest_3.0xD = 0.34
70132.97536001515
cohen score is : ISIBurstMeanChangeTest_3.0xD = -1.03
178302578.85095984
cohen score is : peak_index_3.0xD = -0.60
178241584.288872
cohen score is : threshold_index_3.0xD = -0.60
178530810.96642792
cohen score is : fast_trough_index_3.0xD = -0.60
175527952.76589105
cohen score is : peak_index_1.5xD = -0.52
175512116.83542085
cohen score is : upstroke_index_1.5xD = -0.52
22931026.072419703
cohen score is : AP_fall_indices_1.5xD = 1.61
Features with where models and data disagree, good candidates for optimisation¶